General Linear Model Analysis Research Articles

Determinants of Farmers’ Perceptions towards Socioecological Benefits of Agroforestry Practices in Northwestern Ethiopia

Agroforestry practices provide multiple ecosystem services in agricultural landscapes. However, within the local context, local communities hold divergent perceptions regarding the various roles of agroforestry, particularly in the Afrotropical Region. Hence, understanding these drivers is critical for adopting and promoting sustainable agroforestry practices. Here, we examined the factors that influenced farmers’ perceptions towards the socioecological benefits of agroforestry practices. A multistage stratified random sampling technique was applied to select 90 households along an urban-rural gradient. The data were gathered through semi-structured questionnaires and key informant interviews and analyzed using a descriptive statistics, chi-square tests, general linear model, and redundancy analysis with the help of R software version 4.3.2. The findings showed that approximately 69.7% of the respondents strongly agreed that agroforestry practices had benefits for society and the environment. However, 11.1% were neutral, and the others disagreed. The results of the general linear model analysis showed that household age, agricultural experience, access to land certification books, and training on tree conservation had a significantly positive effect on farmers’ perceptions of the advantages of agroforestry practices. Furthermore, farmers’ perceptions of the benefits of agroforestry in terms of income generation, educational and cultural values, and climate change mitigation were dependent on household age and farming experience. Overall, this study provides useful insights into the drivers of farmers’ perceptions of the advantages of agroforestry practices in Northwest Ethiopia. The findings of this study underscore the need for policymakers and practitioners to consider sociodemographic and institutional factors that influence farmers’ perceptions when developing policies and plans to advance the adoption and promote sustainable management of agroforestry practices. This supports the widespread adoption of agroforestry practices in tropical agroecosystems.

Co-occurrence and abundance of pollinators and pests in horticultural systems in Africa using an integrated Earth observation-based approach

ABSTRACT Flower-visiting insects that are pollinators play a critical role in promoting biodiversity in agroecosystems and agricultural food production through their pollination ecosystem service. However, several factors affect the survival of these pollinators and flower visitors, including the heavy and indiscriminate application of agrochemicals to control crop insect pests, which is impacted by various cropping patterns in a landscape and by shifting environmental conditions. Thus, this study focused on investigating the influence of cropping patterns on the spatial distribution of pollinators (Apis mellifera, Hymenoptera other than A. mellifera, and Syrphidae), flower visitors (Calliphoridae), and pests, i.e. fruit fly (Bactrocera dorsalis) and false codling moth (Thaumatotibia leucotreta) of the avocado, a pollinator-dependent crop. Cropping patterns, earth observation data and relevant environmental variables were used as the predictor variables for modeling the potential distribution and abundance of avocado pollinators, flower visitors and pests in one of the leading regions in avocado production in Kandara, Maragua, and Gatanga sub-Counties in Murang’a County, Kenya. In specific, species distribution modeling (SDM) and species abundance modeling (SAM) techniques, i.e. the maximum entropy (MaxEnt) model (presence-only data) and negative binomial (NB) distribution in a generalized linear model (GLM) (abundance data) were used, respectively. Additionally, the spatial distribution probability of the co-occurrence of the pollinators, flower visitors and pests was also analyzed. This study revealed that cropping patterns was the most consistent influential predictor variables for the distribution of avocado pollinators, flower visitors and pests. A large area of Kandara and some parts of Maragua and Gatanga sub-Counties showed a high spatial distribution probability of the studied avocado pollinators, flower visitors and pests. However, only the majority of Kandara sub-County had a high spatial distribution probability score of the potential co-occurrence of the avocado pollinators, flower visitors and pests. Further, A. mellifera was the most abundant flower-visiting pollinator compared with the other studied pollinators, while B. dorsalis was the most abundant avocado pest compared with T. leucotreta. In addition, GLM analysis indicated that no environmental variable was significant in explaining the abundance of the studied avocado pollinators, whereas precipitation and elevation derivatives of aspect and hillshade were statistically significant (p ≤ 0.05) in explaining the abundance of B. dorsalis. Solar radiation was significant in explaining only the abundance of T. leucotreta. Our study revealed that SDM and SAM modeling outputs can be used to inform decision-making for the implementation of sustainable management efforts regarding pollinators, flower visitors, and insect pests.

Nurses' Personality Traits and Perceived Work Environments During Public Health Emergencies: Implications for Nursing Workforce Planning.

The nursing workforce faces substantial challenges, particularly in the aftermath of the COVID-19 era. Developing an effective strategy for workforce maintenance and the strategic deployment of nurses is crucial. This study aimed to explore and categorize nurses' personality traits, with a focus on analyzing differences in their perceptions of the nursing work environment. Between January 2023 and February 2023, a multi-center cross-sectional study was carried out involving nurses from 12 tertiary hospitals actively engaged in frontline COVID-19 response duties. Through cluster sampling, surveys were distributed among eligible nursing staff, comprising a general information questionnaire, the Chinese Big Five Personality Questionnaire-Short Form, subjective evaluations of emergency nursing management, and the Chinese Nursing Work Environment Scale for Public Health Emergencies. Various statistical analyses, such as descriptive analysis, cluster analysis, non-parametric tests, and general linear model analysis, were employed to investigate the correlation between personality types and the perception of nursing work environments. The analysis encompassed 1059 valid questionnaires, reflecting the experiences of frontline nurses. The majority of these nurses possessed 1-5 years of experience, held junior professional titles, volunteered for their roles, and served as attending nurses. Categorization based on personality traits revealed three groups: resilient (35.60%), ordinary (16.15%), and distressed (48.25%) types. Significantly distinct perceptions of nursing work environments emerged among these categories, with resilient and ordinary types expressing notably higher satisfaction compared to the distressed group (H value = 256.487, p < 0.001). This study illustrates the connection between nurses' perceived working environment and their personality traits. Nursing managers should factor in nurses' personality traits when choosing and deploying frontline responders during public health emergencies. Prioritizing resilient-type nurses and crafting a supportive work environment that aligns with nurses' characteristics is indispensable for an effective emergency response.

Women's Knowledge, Attitudes, and Perception on Personalized Risk-Stratified Breast Cancer Screening: A Cross-Sectional Study in Malaysia.

Breast cancer is commonest cancer among Malaysian women and screening is essential for the early detection. Therefore our study aimed at measuring the levels of knowledge, attitude and perception towards personalized risk stratified breast cancer screening in Malaysia. A cross-sectional study was carried out in Malaysia to assess the knowledge, perception and attitudes of the women in Malaysia. The study was conducted using an online questionnaire, and samples were obtained using convenience sampling. The questionnaire was distributed trilingual in English, Bahasa Malaysia and Chinese. The data was collected with content validated questionnaire. Data was analyzed with descriptive statistics and General Linear Model analysis in SPSS (Version 27). A total of 201 respondents' data were analyzed. From our study we were able to summarize that the women in Malaysia have a suboptimal knowledge towards personalized risk-stratified breast cancer screening as only 48.9% aware of the term for personalized risk-stratified breast cancer screening. Meanwhile, the majority of the respondents (96.7%) showed positive attitudes towards the importance of risk assessment and screening. Experience of participating in health education programmes about breast cancer and personalized risk-stratified screening was found to be significantly associated with knowledge, attitude and perception towards personalized risk-stratified breast cancer screening. General population's awareness of individualized risk-stratified breast cancer screening was insufficient despite their favourable attitude towards the disease. A multimodal strategy may be used to improve women's knowledge, attitude, and perception of individualized risk-stratified breast cancer screening.

Influence of season and photoperiod in severe dog attack cases on humans in a Mediterranean climate region

Dog bites in humans are a serious public health problem widely documented. Although some studies report a seasonal effect on dog bite incidence, the rationale for these findings is poor. This study aimed to describe the influence of season and photoperiod on incidence of dog-bite injury hospitalizations (DBIH) in Sicily, a Mediterranean climate region, over ten years (2012-2021). Four hundred and forty-nine cases of severe dog bites that required hospitalizations were analysed. Patients were divided into two age groups: Group 1 (0-19 years) and Group 2 (≥ 20 years). A Poisson regression general linear model (GLM) analysis was used to model incidence data across seasons and photoperiods (short photoperiod=SP and long photoperiod=LP). The results revealed that the relative risk for Group 1 is higher during summer (2.03; 95%CI 1.30-2.17) and, in general, during LP (1.788; 95%CI 1.274-2.55) when compared with autumn and SP, respectively. Comparing Group 2 with Group 1 a lower relative risk is observed in both summer (0.42; 95%CI 0.28-0.63) and spring (0.32; 95%CI 0.22-0.45), that is almost 60 and 70 per cent lower, and in LP (0.41; 95%CI 0.31-0.53), that it is 60 per cent lower. In Group 2, results showed a significant increase of DBIH during winter and autumn (P<0.05) and in both photoperiods with a positive trend over ten years (P<0.05). Results from this study suggest an influence of season on DBIH modulated by the age of patients. Results are relative to a climatic region that has been characterized by an increase in the intensity of extreme precipitation, especially for the shortest durations in autumn and in winter. This aspect should be considered in developing preventive approaches for dog bite injuries.

Interactions Between Endocannabinoid and Endogenous Opioid Systems Prospectively Influence Postoperative Opioid Use in Pregnant Patients Undergoing Cesarean Delivery

Both endocannabinoid (EC) and endogenous opioid systems are involved in nociceptive processing and may work together synergistically based on preclinical models. This study evaluated the interactive effects of preoperative beta-endorphin concentrations (a key analgesic endogenous opioid) in cerebrospinal fluid (CSF) and ECs (CSF and plasma 2-arachidonoylglycerol [2-AG] and plasma anandamide [AEA]) on postoperative opioid use and pain intensity in a prospective cohort of n = 112 pregnant patients undergoing scheduled cesarean delivery. Maternal blood and CSF samples were collected preoperatively for beta-endorphin and EC assays. Patients completed measures of outpatient opioid use (number of tablets used and days of use) and average pain intensity at 2 weeks postoperatively. Results of general linear model analyses controlling for maternal age, BMI at time of delivery, and race revealed significant multiplicative interactions between EC and beta-endorphin concentrations on number of opioid tablets used (based on pill count), days of opioid use, and total milligram morphine equivalents used in the 2 week follow-up period. Elevated preoperative plasma and CSF 2-AG predicted reduced outpatient opioid analgesic use particularly for patients low in CSF beta-endorphin. Similar analyses for pain intensity at 2-week follow-up indicated a significant interaction (p<.02) characterized by higher preoperative beta-endorphin concentrations being associated with lower subsequent pain only for individuals with low preoperative plasma AEA concentrations. Further exploration of interactions between EC and endogenous opioid inhibitory systems as they influence responses to opioid analgesics in other clinical pain populations may help guide development of precision pain management approaches. PerspectiveIn the postoperative setting of patients undergoing cesarean delivery, elevated endocannabinoids were linked to reduced outpatient opioid analgesic use in individuals who had low endogenous opioid concentrations in cerebrospinal fluid. Further exploration of interactions between these two inhibitory systems as they impact on responses to pain management interventions appears warranted.

Localizing apraxia in corticobasal syndrome: a morphometric MRI study.

Apraxia localization has relied on voxel-based, lesion-symptom mapping studies in left hemisphere stroke patients. Studies on the neural substrates of different manifestations of apraxia in neurodegenerative disorders are scarce. The primary aim of this study was to look into the neural substrates of different manifestations of apraxia in a cohort of corticobasal syndrome patients (CBS) by use of cortical thickness. Twenty-six CBS patients were included in this cross-sectional study. The Goldenberg apraxia test (GAT) was applied. 3D-T1-weighted images were analyzed via the automated recon-all Freesurfer version 6.0 pipeline. Vertex-based multivariate General Linear Model analysis was applied to correlate GAT scores with cortical thickness. Deficits in imitation of meaningless gestures correlated with bilateral superior parietal atrophy, extending to the angular and supramarginal gyri, particularly on the left. Finger imitation relied predominantly on superior parietal lobes, whereas the left angular and supramarginal gyri, in addition to superior parietal lobes, were critical for hand imitation. The widespread bilateral clusters of atrophy in CBS related to apraxia indicate different pathophysiological mechanisms mediating praxis in neurodegenerative disorders compared to vascular lesions, with implications both for our understanding of praxis and for the rehabilitation approaches of patients with apraxia.

Strategic Design Approaches for Eliciting the Perception of ‘Prestige’ in Housing Consumers

In the current real estate landscape, there is a growing trend to focus on adding value to products to address the customer’s affective/emotional perspective, his/her perceptions of the ‘Prestige’ of properties being crucial for his/her final assessments of the products. This study delves into the design elements that shape perceptions of ‘Prestige’ using Kansei engineering in 235 participants who evaluated various real estate promotions through: (1) a set of 60 adjectives and (2) reason for purchase (residence or investment). A first factor analysis of the set of adjectives yielded 15 independent axes. A subsequent linear regression indicated that the ‘Prestige’ axis was among the four most important factors in/drivers of property purchase decisions. In the second phase, 62 design elements (and their respective categories) of real estate promotions were identified to establish 16 groups. A linear regression determined that Information presentation and Building were the groups of elements with the greatest impact on subjects’ perceptions of ‘Prestige’. A subsequent Univariate General Linear Model analysis identified the design elements significant for each group, such as Development type and Building shape, respectively. Finally, a Bonferroni post hoc test identified the important categories in each identified design element as Facing blocks and Stepped.

Robustness of the self-referential process under normobaric hypoxia: an fNIRS study using the GLM and homologous cortical functional connectivity analyses.

Hypoxia has been reported to impair psychological functions, such as working memory and decision-making. However, few studies have examined hypoxia's effect on social cognition. Using a self-referential task, the present study investigated normobaric hypoxia's effect on the self-referential process. Additionally, we measured brain activity during the task with fNIRS and performed conventional univariate analysis with the general linear model (GLM) as well as homologous cortical functional connectivity analysis. The results revealed that normobaric hypoxia impaired recognition of adjectives in the other-reference condition but not in the self-reference. The GLM analysis did not detect differences in brain activity between the self- and other-reference conditions, suggesting that GLM analysis may not be suitable for examining self- and other-reference conditions' neural correlates. The homologous cortical connectivity analysis revealed that the connectivity's magnitude was greater in the self-reference than in the other-reference conditions in the normoxic group. However, such a decrease in connectivity in the other-reference conditions was not observed in the hypoxic group, possibly to compensate for cognitive decline induced by the hypoxia. Considering that homologous connectivity reflects the default mode network, which is supposedly linked to continuous self-reference, stable strength of the connectivity in the self-reference condition under the hypoxia may suggest robust nature of the self-reference process under normobaric hypoxia.

Functional reorganization of memory processing in the hippocampus is associated with neuroprotector GLP-1 levels in type 2 diabetes

Type 2 diabetes (T2D) often impairs memory functions, suggesting specific vulnerability of the hippocampus. In vivo neuroimaging studies relating encoding and retrieval of memory information with endogenous neuroprotection are lacking. The neuroprotector glucagon-like peptide (GLP-1) has a high receptor density in anterior/ventral hippocampus, as shown by animal models. Using an innovative event-related fMRI design in 34 participants we investigated patterns of hippocampal activity in T2D (n = 17) without mild cognitive impairment (MCI) versus healthy controls (n = 17) during an episodic memory task. We directly measured neurovascular coupling by estimating the hemodynamic response function using event-related analysis related to encoding and retrieval of episodic information in the hippocampus. We applied a mixed-effects general linear model analysis and a two-factor ANOVA to test for group differences. Significant between-group differences were found for memory encoding, showing evidence for functional reorganization: T2D patients showed an augmented activation in the posterior hippocampus while anterior activation was reduced. The latter was negatively correlated with both GLP-1 pre- and post-breakfast levels, in the absence of grey matter changes. These results suggest that patients with T2D without MCI have pre-symptomatic functional reorganization in brain regions underlying episodic memory, as a function of the concentration of the neuroprotective neuropeptide GLP-1.

Prediction of image interpretation cognitive ability under different mental workloads: a task-state fMRI study.

Visual imaging experts play an important role in multiple fields, and studies have shown that the combination of functional magnetic resonance imaging and machine learning techniques can predict cognitive abilities, which provides a possible method for selecting individuals with excellent image interpretation skills. We recorded behavioral data and neural activity of 64 participants during image interpretation tasks under different workloads. Based on the comprehensive image interpretation ability, participants were divided into two groups. general linear model analysis showed that during image interpretation tasks, the high-ability group exhibited higher activation in middle frontal gyrus (MFG), fusiform gyrus, inferior occipital gyrus, superior parietal gyrus, inferior parietal gyrus, and insula compared to the low-ability group. The radial basis function Support Vector Machine (SVM) algorithm shows the most excellent performance in predicting participants' image interpretation abilities (Pearson correlation coefficient = 0.54, R2 = 0.31, MSE = 0.039, RMSE = 0.002). Variable importance analysis indicated that the activation features of the fusiform gyrus and MFG played an important role in predicting this ability. Our study revealed the neural basis related to image interpretation ability when exposed to different mental workloads. Additionally, our results demonstrated the efficacy of machine learning algorithms in extracting neural activation features to predict such ability.

Prevalence and predictors of high-frequency hearing loss among mine workers in Gujarat, western India: a cross-sectional study on the need to implement a comprehensive hearing conservation program.

High-frequency hearing loss (HFHL) stands as a prevalent occupational morbidity globally, with numerous associated risk factors, some of which are modifiable. In the context of a comprehensive hearing conservation program, the initial steps involve early screening and identification of workers with these modifiable risk factors, aiming to reduce the prevalence of hearing loss. Our objective was to estimate the prevalence of HFHL and determine its predictors among mine workers. We conducted a cross-sectional study among 226 mine workers in ten open-cast mines in Gujarat state, the western part of India, in November 2020. We collected data on socio-demography, addiction, occupation history and comorbidities, along with anthropometric, blood pressure, and blood sugar measurements. Audiometric evaluations using a portable diagnostic audiometer were employed to assess HFHL, defined as a hearing threshold exceeding 25 decibels (dB) at high frequencies (3000, 4000, 6000, and 8000Hz). A generalized linear model (GLM) with a binomial family was performed to determine the predictors significantly predicting HFHL after adjusting for confounding variables. The prevalence of HFHL was 35% (95% CI: 29-42%) in our study setting. Office workers demonstrated a prevalence of 19%, whereas other job categories displayed a higher prevalence of 42%, resulting in a significant prevalence difference of 23% and a prevalence ratio of 2.2. The GLM analysis revealed that variables, such as noise exposure during work [adjusted prevalence ratio (aPR) 2.3 (95% CI: 1.2-4.7, p=0.018)] and noise exposure duration [aPR 1.1 (95% CI: 1.0-1.1, p=0.042)], were significant predictors of HFHL. In our study setting, mine workers exhibited a high prevalence of HFHL, with exposure to workplace noise and duration being modifiable predictors. Because HFHL advances slowly and is generally undetected by the individual, we recommend periodic testing using audiometry to identify it among mine workers and, if possible, shifting them from mining activities to office. Furthermore, we advocate for the implementation of a comprehensive hearing conservation program to the extent possible.

Sleep duration has a limited impact on the prevalence of menstrual irregularities in athletes: a cross-sectional study.

This study aimed to investigate the relationship between the prevalence of menstrual irregularities, energy intake, and sleep deprivation among female athletes. A total of 128 female athletes, with an average age of 19.2 ± 1.2 years, participated in the study and tracked their food intake over a three-day period. Menstrual status and sleep duration were assessed using a questionnaire, and psychological anxiety was evaluated using the State and Trait Anxiety Inventory (STAI). These were measured once during the investigation. The impact of sleep status on state anxiety and daily energy intake was examined using the T-test. A generalized linear model (GLM) with a log link function was employed to investigate the effects of sleep deprivation on the presence of menstrual irregularities. As the results of the present study, sleep deprivation significant increased both state and trait anxiety (p < 0.05), as well as affecting energy intake (p < 0.05), particularly protein and carbohydrate intakes (p < 0.05). However, GLM analysis indicated that while sleep deprivation did not directly influence the prevalence of menstrual irregularities (p > 0.05), state anxiety emerged as a significant factor impacting the prevalence of menstrual irregularities (p < 0.05). The results of the present study suggest a potential pathway wherein sleep deprivation might elevate state anxiety levels, consequently indirectly contributing to an increase the probability of menstrual irregularities. In conclusion, the results of the presents study provide novels insights suggesting that sleep deprivation might directly increase state anxiety and indirectly affect the prevalence of menstrual irregularities. Hence, decreased sleep duration might be related to mental health issues and the prevalence of menstrual irregularities both significant concerns among female athletes. Future studies will play a crucial role in further elucidating how sleep patterns impact the health and well-being of female athletes.

Characterizing the Dynamics of Virulence and Fungicide Resistance of Phytophthora capsici in Michigan Vegetable Fields Reveals Loci Associated with Virulence.

The oomycete Phytophthora capsici is a destructive pathogen infecting more than 50 plant species and is one of the most serious threats to cucurbit production. Phytophthora blight caused by Phytophthora capsici can affect all plant growth stages, and fungicides and cultural controls are used to limit losses. Dissecting pathogen virulence and fungicide resistance can provide insights into pathogenic mechanisms and inform effective management practices to control P. capsici. In this study, we assessed virulence, mefenoxam sensitivity, and genetic diversity of nine P. capsici populations collected from Cucurbitaceae, Solanaceae, and Fabaceae host families in Michigan from 2002 to 2016. We developed 992 simple sequence repeats (SSRs) in the P. capsici genome and identified 60 SSRs located within or close to RXLR-class (Arginine-any amino acid-Leucine-Arginine) effectors and 29 SSRs within or close to effector CRN (CRinkling and Necrosis) family protein, which represent 62 RXLR and 34 putative CRNs. Population structure analysis shows that mefenoxam resistance was not associated with the year of collection, host type, or location, but there were significant differences in virulence among the populations. Using the general linear model and mixed linear model-based association analyses with all effector-related SSR markers, we identified four SSR markers significantly associated with at least one of the virulence-related parameters. Of these, one (Pce_SC18) was in a predicted CRN effector and had high identity with the putative PhCRN37 effector in the pathogen Plasmopara halstedii, which can be further verified for virulence identification in P. capsici.

P1144 Forecasting the Future Prevalence of Inflammatory Bowel Disease in Korea through 2048: An Epidemiologic Study Employing Autoregressive Integrated Moving Average Models

Abstract Background The global escalation of Inflammatory Bowel Disease (IBD) has precipitated an increased burden of disease and economic impact, particularly accentuated within the Asian context. The primary objective of this study is to predict the future prevalence trajectory of IBD in Korea and elucidate the pattern of its evolution. Methods Data from the Korean National Health Insurance Service (2004–2018) were analyzed using a validated diagnostic algorithm to identify IBD patients. An autoregressive integrated moving average (ARIMA) model, employing 2004–2017 data, predicted future trends based on past values and error correction. The model's accuracy was validated against the actual 2018 patient count. We projected IBD patient numbers and prevalence from 2018 to 2048, using a generalized linear model (GLM) to determine influencing factors. Results A consistent annual increase in the number of IBD cases across all age groups was observed from 2004 to 2018, with prevalence peaking in the 20–39 age group. The validation of our prediction model demonstrated an acceptable range of error for IBD prevalence, with a 2.45% error rate and a mean absolute difference of 2.61. The 2018–2048 projections confirm a steady rise in Crohn’s disease (CD), ulcerative colitis (UC), and IBD prevalence across both genders (Figure 1). IBD prevalence is projected to increase from 104.19 per 100,000 in 2018 to 149.59 per 100,000 by 2028, and further to 239.73 per 100,000 by 2048 (95% confidence interval [CI]: 223.73–255.73), marking a 130% increase. By 2048, the prevalence rates for UC and CD were estimated to be 159.40 per 100,000 (95% CI: 137.38–181.42) and 91.11 per 100,000 (95% CI: 0.81–181.41), respectively. The Average Annual Percent Change (AAPC) of IBD is predicted at 4.51%, varying from a 2.77% decrease in those over 60 to a 14.20% increase in the 20–39 age group. Gender-stratified forecasts show a higher AAPC in males (6.17%) compared to females (2.75%) over the next 30 years. The highest AAPC, valued at 19.48, was noted in the male group aged 20–39 years. GLM analysis indicates significant age, gender, and temporal effects on IBD prevalence, with marked gender disparities in specific age groups for both CD and UC. In UC, males aged 20–39 experienced a significantly higher increase in prevalence than females. For CD, males also showed a higher prevalence increase than females in the 20–39 and 40–59 age groups (all interaction p-values &amp;lt; 0.05; Table 1). Conclusion This study forecasts a significant increase in Korean IBD prevalence by 2048, especially among males and the 20–39 age group, highlighting the need to focus on these high-risk demographics in future disease management.

Forecasting the future prevalence of inflammatory bowel disease in Korea through 2048: an epidemiologic study employing autoregressive integrated moving average models.

The global inflammatory bowel disease (IBD) escalation has precipitated an increased disease burden and economic impact, particularly in Asia. This study primarily aimed to predict the future prevalence of IBD in Korea and elucidate its evolution pattern. Using a validated diagnostic algorithm, we analyzed data from the Korean National Health Insurance Service between 2004 and 2017 to identify patients with IBD. We predicted the number and prevalence of patients with IBD from 2018 to 2048 with the autoregressive integrated moving average method. A generalized linear model (GLM) was also employed to identify factors contributing to the observed trend in IBD prevalence. Our prediction model validation demonstrated an acceptable error range for IBD prevalence, with a 2.45% error rate and a mean absolute difference of 2.61. We foresee a sustained average annual increase of 4.51 IBD cases per 100 000, culminating in a prevalence of 239.73 per 100 000 by 2048. The forecasted average annual percent change was 6.17% for males and 2.75% for females over the next 30years. The GLM analysis revealed that age, gender and time significantly impact the prevalence of IBD, with notable disparities observed between genders in specific age groups for both Crohn's disease and ulcerative colitis (all interaction P<0.05). Our study forecasts a notable increase in Korean IBD prevalence by 2048, particularly among males and the 20-39 age group, highlighting the need to focus on these high-risk groups to mitigate the future disease burden.

Morphological Variations and Path Coefficient Analysis of Zoometric Traits of Local Chickens in Tolon District of Northern Ghana

The knowledge of morphometric measurements is paramount in domestic chicken production and marketing practices hence this research was undertaken to determine the morphological characteristics of domestic chicken in the Tolon District of Ghana. Birds reared under the traditional scavenging system, were randomly selected in four (Nyankpala, Tolon, Woribogu and Dondo) communities. Live body weight (BW) and thirteen morphometric traits namely, body length (BDL), chest circumference (CC), thigh circumference (TC), drumstick length (DL), shank length (SL), wing length (WGL), neck length (NL), head width (HDW), hip width (HPW), comb length (CL), head length (HDL), wattle length (WAL) and beak length (BKL) were measured. The data was subjected to general linear model, correlation and path coefficient analyses. The results revealed that, domestic chickens were generally smaller in sizes. The average values recorded were 0.99kg, 18.98cm, 20.60cm, 7.78cm, 11.78cm, 8.05cm, 16.17cm, 12.15cm, 2.34cm, 7.57cm, 3.39cm, 2.28cm, 1.70cm and 2.60cm for BW, BDL, CC, TC, DL, SL, WGL, NL, HDW, HPW, CL, HDL, WAL and BKL respectively. Location of birds significantly (P&lt; 0.05) affected morphometric traits (BDL, CC, TC, SL, WGL, NL, HDW, CL, HPW, and WAL) of birds. Similarly, sex of birds had significant (P&lt;0.05) effects on BDL, DL, SL, WGL, NL, HDW, CL, HDL, WAL and BKL whereas age had no significant (P&gt;0.05) influence on any morphometric traits. The presence of crest affected (P&lt;0.05) the variations in DL, SL, WAL and BKL. Also, presence of spur affected the variations (P&lt;0.05) in BW, DL, NL, CL, HDL, WAL and BKL whiles comb type had no significant (P&gt;0.05) effects on any morphometric trait. Correlation coefficients were generally low, with the highest (0.513) recorded between TC and CC. The highest direct path coefficient was obtained from CC (0.237), followed by BDL (0.156) and WAL (0.153). The findings of this work will be useful in characterization studies and breeding program for local domestic chickens.

Experimental Investigation of Infill Parameters Influence on Compressive Strength-to-Mass Ratio of PLA 3D Printed Part

An infill pattern can be implemented in manufacturing a porous component using 3D Printing technology to reduce the mass of the printed part. The use of an infill pattern and infill angle affects the structure of the printed part. This research aims to investigate the effect of various infill patterns and angles on the compressive strength-to-mass ratio of components manufactured by 3D Printing. This research implements a General Linear Model analysis with two replications. Seventy-two compressive test specimens, according to ASTM D695, are printed and tested for compression. The experiment results show that the type of infill pattern has a significant effect on the mass. However, the mass is not significantly influenced by the infill angle. In addition, the infill pattern type and the infill angle significantly influence the compressive strength of the specimen. Then, the compressive strength-to-mass ratio is significantly affected by the infill patterns and angles. The results indicate that a part using the Honeycomb infill pattern type gains the highest compressive strength-to-mass ratio compared to other infill patterns. On the opposite, the infill pattern that creates the lowest compressive strength-to-mass ratio compared to other infill patterns is the Archimedean chords type. The use of a 45° infill angle causes the lowest compressive strength-to-mass ratio compared to other infill angles. Using a 90° infill angle causes the highest compressive strength-to-mass ratio compared to other infill angles.

Trace elements in tea in Ouargla, Algeria and health risk assessment

ABSTRACT Tea is one of the most common drinks, consumed for its pleasant flavour and several medicinal values. The present study aimed to determine the levels of trace elements in tea products marketed in the Saharan region of Ouargla, Algeria and to evaluate the health risks associated with its regular consumption in adults and infants. To this aim, 78 tea samples were analysed by Inductively Coupled Plasma – Mass Spectrometry. Tea samples appeared to be contaminated by lead (0.73 ± 0.08 µg g−1) and aluminium (0.22 ± 0.02 µg g−1). Cadmium, arsenic, mercury, cobalt, manganese, nickel, chromium, zinc and copper were also detected. General linear model analysis indicated that black tea samples were the most contaminated. Tea samples packed in tea bags were the most contaminated with arsenic, aluminium and manganese. The hazard index was 0.28 and 1.33 for adults and for infants, respectively, indicating adverse non-carcinogenic effects in infants.

Vitamin D status and its associations with bone mineral density, bone turnover markers, and parathyroid hormone in Chinese postmenopausal women with osteopenia and osteoporosis.

Vitamin D is a key factor in bone metabolism, yet vitamin D insufficiency and deficiency are prevalent among postmenopausal women, with potential repercussions on bone mineral density (BMD), bone turnover markers (BTMs), and parathyroid hormone (PTH). Nonetheless, the findings from existing studies exhibit inconsistency, and a notable gap exists in the availability of large-scale investigations. In this real-world study, 8,532 postmenopausal women over 50 years old with a diagnosis of osteopenia (50.9%) and osteoporosis (49.1%) at the first visit were enrolled in this study. Serum 25(OH)D level, PTH, osteocalcin (OC) and Beta-CrossLaps of type 1 collagen containing cross-linked C-telopeptide (β-CTX), were measured. BMD at all sites, including the lumbar spine, femoral neck, and total hip were obtained by dual-energy X-ray absorptiometry (DXA). The associations of serum 25(OH)D level with BMDs and BTMs were investigated using spearman correlation analysis and analysis of general linear model adjusted by age and body mass index. The serum 25(OH)D level was 22.17 ± 9.75 ng/mL among all patients included in this study. For the osteopenia group, the serum 25(OH)D level was 22.40 ± 9.41 ng/mL, while for the osteoporosis group, it measured 21.93 ± 10.08 ng/mL. In the osteopenia group, the prevalence of vitamin D deficiency, insufficiency and sufficiency was 45.8, 34.6, and 19.6%, respectively, which was close to that of the osteoporosis group (47.4, 34.3, and 18.3%) (p = 0.202). Spearman correlation analysis unveiled negative associations between serum 25(OH)D concentrations and both BTMs and PTH within both the osteopenia and osteoporosis group. In the osteoporosis group, there were positive correlations between 25(OH)D levels and femoral neck BMD (r = 0.040, p = 0.010) and total hip BMD (r = 0.053, p = 0.001). Furthermore, we found that for the osteopenia group, greater vitamin D levels were associated with greater femoral neck BMD (p = 0.020) and total hip BMD (p = 0.008) and lower β-CTX (p < 0.001), OC (p < 0.001), and PTH (p < 0.001). The same trends were seen in osteoporosis patients (p < 0.05), and with greater lumbar spine BMD with higher levels of 25(OH)D (p = 0.009). This study showed high prevalence of vitamin D deficiency and insufficiency in Chinese postmenopausal women with osteopenia and osteoporosis and the relationships between vitamin D and BMD, BTMs and PTH. The results contribute to a more comprehensive understanding of how vitamin D may impact bone health.